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Full Description
Fog computing is a decentralized computing infrastructure in which computing resources are located between the data source and the cloud or any other data centers. The word "fog" refers to its cloud-like properties, which are closer to the "ground", using edge devices that carry out locally computation, storage and communication tasks. An additional benefit is that the processed data is likely to be needed by the same devices that generated the data. By processing locally rather than remotely, the latency between input and response are minimized. This technology has countless application domains such as industrial process control, smart cities, transportation, healthcare and agriculture.
In this book, all the important topics in fog computing systems are covered, including energy efficiency, quality of service (QoS) issues, reliability and fault tolerance, load balancing, and scheduling. Special attention is devoted to emerging trends and industry needs associated with utilizing mobile edge computing, internet of things (IoT), resource estimation as well as virtualization in the fog computing environment. Current research on automation, robotics, data privacy, security and trust in fog computing is explored in depth. The book also discusses emerging techniques including deep learning, mobile edge computing, smart grid and intelligent transportation systems beyond theoretical and foundational concepts for smart applications including real time traffic surveillance, interoperability of fog computing architecture and smart homes and smart cities.
Intended for an audience of researchers from academia and industry, as well as lecturers, engineers and advanced students, Enabling Technologies for Smart Fog Computing offers valuable insights for those with an interest in the field.
Contents
Chapter 1: Introduction of fog computing
Chapter 2: Fog computing in the IoT environment
Chapter 3: Enhance quality of fog-computing environment using SDN and NFV technology
Chapter 4: Using P2P pervasive grid improves tunneling architecture and routing scalability
Chapter 5: Vehicular fog computing and virtualization
Chapter 6: Smart XSS attack surveillance system for fog computing
Chapter 7: Spectral image analysis with supervised feature extraction
Chapter 8: Developing of fog computing using sensor data
Chapter 9: Information sharing on mobile IoT-based content aware smart home with fog computing
Chapter 10: Security and privacy challenges in fog computing
Chapter 11: Fog robotics
Chapter 12: Cybernetic intelligence in fog computing
Chapter 13: Further application of fog computing
Chapter 14: Future research directions
